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01/10/2025
Location: Netanya
Job Type: Full Time
We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our machine learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind.
You will work closely with data scientists, machine learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance.
Key Responsibilities:
Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators.
Support reproducibility and consistency across model training environments.
Implement and manage Artifactory.
Establish and maintain model registries to track versions, metadata, and lineage.
Automate model promotion through staging, testing, and production environments.
Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback.
Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments.
Optimize GPU/CPU resource utilization and cost efficiency.
Implement auto-scaling and load balancing strategies for ML workloads.
Manage version control systems (e.g., Git) and integrate with experiment tracking tools.
Handle storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.
Requirements:
3+ years of experience in MLOps, DevOps, or related engineering roles.
Hands-on experience with ML pipelines and orchestration tools (e.g., MLflow, Airflow, Kubeflow).
Proficiency with Docker, Podman, Kubernetes, and containerized deployments.
Experience with cloud platforms Azure (AWS/GCP) and hybrid infrastructure setups (on-prem + cloud).
Strong understanding of model versioning, packaging, and deployment best practices.
Solid knowledge of Git, CI/CD tools (e.g., Jenkins, GitHub Actions, BitBucket pipelines), and monitoring stacks.
Proficiency in Python, Bash, and infrastructure tools.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an ML Engineer to join our Data department. In this role, you will be responsible for the infrastructures needed to train models, serve them and do other ML magic.
What Youll Do:
Develop, integrate and optimize end-to-end ML solutions (data pipelines, training workflows, and serving infrastructure)
Plunge into a world of data, analytics, ML, high-paced and high-scale user and market movements
Work closely with Data Scientists to understand the business from top-to-bottom and turn their dreams into reality
Requirements:
4+ years of professional experience in Software Development or Data Science and 2+ years of experience in ML Ops Engineering/Machine Learning Engineering
Strong experience with Python and Machine Learning libraries
Proficiency with data analysis and feature engineering
Experience developing services and APIs in a cloud based microservices ecosystem
Experience SQL (BigQuery - Bonus)
BSc degree (or higher) in Mathematics, Statistics, Engineering, Computer Science, or any other quantitative field/military experience
Team player as well as the ability to be independent and proactive!
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Required Senior MLOps Engineer - AI Infrastructure
Tel Aviv
As a Senior MLOps Engineer, you will be pivotal in designing, implementing, and maintaining our AI cloud infrastructure. You will join a highly technological team responsible for developing our model-serving platform, optimizing inference, and ensuring reliability and cost efficiency. In this role, you will collaborate with key stakeholders across the company, including product engineering teams, internal clients (both researchers and engineers), and Security and DevOps, to automate processes, streamline operations, and drive impactful changes in our model-serving strategy.
Key Responsibilities:
AI Infrastructure Design & Implementation: Lead the design and implementation of our cloud-native infrastructure, ensuring it is performant, scalable, and cost-effective.
Automation & Streamlining: Help automate and streamline our AI operations and processes, enhancing efficiency and reducing manual intervention.
Cross-Functional Collaboration: Work closely with product engineering teams, including internal clients (both researchers and engineers), security, DevOps, and more, to ensure adoption of our AI platform.
Impactful Contribution: Play a major part in shaping the companys AI serving strategy, focusing on innovation and long-term success.
Requirements:
4+ years as a DevOps/MLOps Engineer, with extensive experience in cloud computing technologies, preferably AWS.
Strong scripting and automation skills, ideally using Python and bash.
Proficiency with Infrastructure as Code (IaC) tools such as Terraform and Terragrunt.
Hands-on experience with GitOps and CI/CD methodologies and tools like ArgoCD, Argo Workflows, GitHub Actions, and Jenkins.
Proven experience working with Kubernetes (K8s) in production environments.
Experienced with common model-serving solutions: Ray/KServe/Triton/HF etc.
Experienced with system observability & monitoring.
A solid understanding of computer networking fundamentals, storage, REST/gRPC architecture.
Excellent communication skills and the ability to execute projects from design to implementation.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
Required Senior ML Backend Engineer
Tel Aviv
As a Senior Machine Learning Backend Engineer, you'll architect and build the high-performance backend systems that power our AI at massive scale, craft real-time ML serving innovative solutions, and play a pivotal role in our mission to revolutionize the way companies understand their customer interactions. We're seeking a Java professional who can leverage their deep knowledge to drive our backend development to new heights.
You will be responsible for:
ML Serving Architecture: Design and implement high-performance inference APIs and model serving backends using Java & Python.
Model Lifecycle Management: Build systems for model versioning, A/B testing, canary deployments, and automated rollbacks.
Integration Platform: Create robust APIs and SDKs that enable product teams to seamlessly integrate AI capabilities.
Observability & Monitoring: Build comprehensive metrics, logging, and tracing systems for ML workloads.
Cross-team Leadership: Mentor engineers & researchers, drive technical decisions, and influence platform architecture across the organization.
Requirements:
6+ years of hands-on experience in large-scale backend development, with strong emphasis on Java programming and building high-performance AI/ML inference systems.
Strong analytical and problem-solving skills, with the ability to debug and resolve complex technical issues in AI applications serving millions of requests daily.
Experience with cloud platforms (AWS preferred, Azure, or Google Cloud) and building scalable microservices architectures for AI model serving and data processing pipelines.
Advantageous experience with ML frameworks (TensorFlow, PyTorch), model serving platforms (Triton, TorchServe, KServe), and building high-throughput AI-powered APIs and data processing systems.
Excellent communication skills, both verbal and written, with the ability to articulate technical AI system design decisions clearly and collaborate effectively with ML engineers, data scientists, and DevOps teams.
A Bachelor's degree in Computer Science, Engineering, or a related field is preferred. Experience with AI/ML systems in production environments is highly valued.
This position is open to all candidates.
 
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Location: Hod Hasharon
Job Type: Full Time
We are a cutting-edge cybersecurity lab dedicated to addressing next-generation threats through advanced AI and machine learning. Our work spans multiple domains, including endpoint protection, cloud security, and AI-driven defense technologies. Our mission is to invent and implement breakthrough solutions that provide Huawei with a strategic edge in the global cyber defense landscape. By bridging research and engineering, our teams transform innovative concepts into real-world solutions that safeguard enterprises and critical infrastructure. We also maintain close collaborations with leading universities and international innovation hubs.
Role Overview
We are seeking a Senior Applied Machine Learning / AI Engineer with at least 5 years of hands-on experience in designing, developing, and deploying machine learning models, specifically for cybersecurity applications. This role combines applied ML engineering with innovation and research, requiring someone who can move seamlessly from proof-of-concept to production, and lead initiatives that drive our AI-driven security strategy.
Key Responsibilities
Lead the design, training, and deployment of advanced ML/DL models for cybersecurity use cases (malware detection, anomaly detection, network behavior analytics, adversarial ML defense, etc.)
Drive innovation by developing proof-of-concepts, exploring novel AI techniques, and translating research findings into practical, scalable solutions
Collaborate with cross-functional teams (security researchers, software engineers, product managers) to bring ML-driven features into production environments
Analyze large-scale, heterogeneous cybersecurity datasets (logs, network traffic, endpoint telemetry, threat intel)
Implement robust model monitoring, explainability, and optimization for real-world environments
Stay at the forefront of advances in AI, data science, and cybersecurity; identify emerging opportunities and mentor junior engineers/researchers
Represent the company in external collaborations, conferences, and innovation forums.
Requirements:
BSc/MSc/PhD in Computer Science, Electrical/Computer Engineering, Data Science, or related field
5+ years of professional experience applying ML/AI in real-world projects (cybersecurity experience highly preferred)
Strong proficiency in Python and ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn)
Proven experience taking ML models from research/prototype to production
Solid background in statistical modeling, anomaly detection, time-series, or NLP for security data
Familiarity with cybersecurity fundamentals: network protocols, threat types, SOC/incident response workflows, malware families, etc.
Experience with cloud environments (AWS, Azure, GCP) and data pipelines (Spark, Kafka, Airflow, etc.)
Strong problem-solving, innovation mindset, and ability to work in fast-paced R&D environments
Preferred / Nice-to-Have
Experience in adversarial machine learning or AI for threat simulation
Background in innovation projects (e.g., patents, published research, leading POCs)
Hands-on experience with graph neural networks, reinforcement learning, or generative AI in security contexts
Experience mentoring or leading small ML teams
Participation in academic collaborations or conference publications (Black Hat, IEEE, NeurIPS, etc.).
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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25/09/2025
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior Machine Learning Engineer to design and build scalable ML models that power critical business decisions. You will focus on building ML expertise from experimentation to production in one or more areas that improve the company's overall ML strategy. This role is based in Tel Aviv and involves collaboration across global teams, requiring strong communication and coordination skills.

Responsibilities:

Build and deploy end-to-end machine learning solutions from research to production by leveraging advanced algorithms and mathematical techniques to deliver highly predictive models in the fintech space.
Design and run experiments to evaluate new data sources and continuously improve the performance of existing models.
Implement, maintain, and monitor production models using machine learning platform, ensuring scalability, reliability, and long-term performance.
Evaluate model effectiveness both offline and in live environments, with a focus on real-world impact and business relevance.
Act as a technical leader, mentoring teammates, guiding design decisions, and collaborating with global cross-functional partners to drive ML initiatives forward.
Requirements:
MSc/Ph.D. in Statistics, computer science, data science or a related field
5+ years of experience of exploring, building and deploying ML and data systems in production
Strong programming skills in Python focusing on ML frameworks such as Sklearn, XGBoost or TensorFlow
Experience with distributed and stream processing, Cloud ML infrastructure and feature store tools
Expertise in supervised and unsupervised machine learning models (e.g., classification, anomaly detection or clustering)
Experience writing code in Agile, CI/CD-based production environments
Proficient in communicating technical and research ideas and collaborating effectively across teams and organizational stakeholders
Experience in Fintech solutions is a big advantage
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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